In the field of communications, particularly wireless voice communications, there is a constant effort to manufacture consumer electronics that allow a clearer signal, such that participants in a communication session can better understand each other. As a result, an incoming communication signal can be filtered to remove unwanted signal power within a given frequency band. As an example, electronic noise and/or interferer signals at frequencies both known and unknown can contribute to such unwanted signal power. Thus, the incoming communication signal can be filtered to attempt to remove the unwanted signal power at specific frequencies in the frequency spectrum of the communication signal.
As the incoming communication signal is first received in the analog domain, some typical filter systems attempt to filter the signal in the analog domain. However, to filter more specific frequencies in the frequency spectrum of a communication signal, analog filter systems can be expensive and bulky, and can involve extremely complicated algorithms to allow them to be tunable to the specific frequency ranges in the frequency spectrum. As incoming communication signals are often converted to the digital domain, some typical filter systems attempt to filter the system in the digital domain. However, while digital filters are typically inexpensive and often involve much simpler algorithms, digital filters may be required to implement extremely high resolution to maintain signal quality of an incoming signal, and can also require an extremely high dynamic range of an upstream analog-to-digital converter (ADC) to be able to receive the incoming signal without losing modulated information. A high dynamic range ADC using existing design techniques is prohibitively expensive, power hungry and bulky, particularly for low-cost and low-power applications, such as mobile stations.
Another manner of filtering that is typically implemented is an adaptive filter algorithm. An adaptive filter algorithm is an algorithm that continuously monitors an output of the adaptive filter to estimate a location of interferer signals. The interferer signals can thus be cancelled based on subtracting power at the estimated locations as the signal is subsequently received. Adaptive filter algorithms, however, are typically very complicated, and can suffer from time delays in filtering the interferers and/or noise, and can be unstable based on the variations and reactions of the filter output. In addition, estimation errors can result in filtering portions of the signal of interest, or possibly undesirably boosting noise and/or interferers based on a lack of convergence of the filter algorithm. As a result, the continuously varying transfer function of the adaptive filter algorithm may not result in accurate filtering of unwanted signal power from a frequency spectrum of an incoming communication signal.